Special Issue "Complex System Theory Applied to Plant Sciences"

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A special issue of Plants (ISSN 2223-7747).

Deadline for manuscript submissions: closed (31 October 2012)

Special Issue Editor

Guest Editor
Prof. Dr. Gustavo Maia Souza

Laboratory of Plant Intelligence and Ecophysiology "Ulrich Lüttge" - LIPEUL, Campus II, Rodovia Raposo Tavares KM 572, Presidente Prudente - SP, CEP - 19067-175, Brazil
Website | E-Mail
Phone: 55 18 3229 2000
Interests: cerrado; complex system biology; ecophysiology; photosynthesis; plant physiology; savanna; stress physiology

Special Issue Information

Dear Colleagues,

Complex System Theory, a new emergent science based on General System Theory of Ludwig von Bertallanfy (1968), is addressed to phenomena that show some special traits such as: network organization with non-linear relations among some elements that constitute the system (complex networks), irregular (complex, eventually chaotic) temporal dynamic, self-organization, and robustness.

As other living system, plants are complex systems hierarchically organized and composed by interactive elements, from molecular to whole plant level, showing some properties that may not be understood by isolated elements, that is, high levels of organization exhibit emergent properties.

Analyses that evaluate interactions among network components can improve predictions of plant behavior under environmental changes. The relationship between complexity and physiological stability has been observed among different kinds of biological systems. In plants, some evidence indicates that more complex temporal dynamics in parameters such as photosynthesis, enzymatic reactions and a broad class of fluxes are associated with a greater capacity of system homeostasis.

Therefore, approaches that assess and quantify such systemic properties, considering the relationships among system elements (networks) and complex dynamics, could play an important role in improving classical physiological knowledge and its methods.

Dr. Gustavo Maia Souza
Guest Editor

Keywords

  • system biology
  • network
  • temporal complex dynamics
  • plant modeling
  • stability
  • robustness
  • chaos
  • fractals
  • thermodynamical open systems
  • sel-organization
  • plant intelligence
  • plant signaling and behavior

Published Papers (3 papers)

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Research

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Open AccessArticle Network Connectance Analysis as a Tool to Understand Homeostasis of Plants under Environmental Changes
Plants 2013, 2(3), 473-488; doi:10.3390/plants2030473
Received: 10 May 2013 / Revised: 2 July 2013 / Accepted: 3 July 2013 / Published: 10 July 2013
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Abstract
The homeostasis of plants under environmental constraints may be maintained by alterations in the organization of their physiological networks. The ability to control a network depends on the strength of the connections between network elements, which is called network connectance. Herein, we intend
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The homeostasis of plants under environmental constraints may be maintained by alterations in the organization of their physiological networks. The ability to control a network depends on the strength of the connections between network elements, which is called network connectance. Herein, we intend to provide more evidence on the existence of a modulation pattern of photosynthetic networks, in response to adverse environmental conditions. Two species (Glycine max-C3 metabolism, and Brachiaria brizantha-C4 metabolism) were submitted to two environmental constraints (water availability, and high and low temperatures), and from the physiological parameters measured, the global connectance (Cgtotal) and the modules connectance (gas exchange-Cgge and photochemical-Cgpho) were analyzed. Both types of environmental constraints impaired the photosynthetic capacity and the growth of the plants, indicating loss of their homeostasis, but in different ways. The results showed that in general the Cgtotal of both species increased with temperature increment and water deficit, indicating a higher modulation of photosynthetic networks. However, the Cg variation in both species did not influence the total dry biomass that was reduced by environmental adversities. This outcome is probably associated with a loss of system homeostasis. The connectance network analyses indicated a possible lack of correspondence between the photosynthetic networks modulation patterns and the homeostasis loss. However, this kind of analysis can be a powerful tool to access the degree of stability of a biological system, as well as to allow greater understanding of the dynamics underlying the photosynthetic processes that maintain the identity of the systems under environmental adversities. Full article
(This article belongs to the Special Issue Complex System Theory Applied to Plant Sciences)
Open AccessArticle Self-Affinity, Self-Similarity and Disturbance of Soil Seed Banks by Tillage
Plants 2013, 2(3), 455-472; doi:10.3390/plants2030455
Received: 22 April 2013 / Revised: 7 May 2013 / Accepted: 1 July 2013 / Published: 5 July 2013
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Abstract
Soil seed banks were sampled in undisturbed soil and after soil had been disturbed by tillage (tine, harrow or plough). Seeds were sorted by size and shape, and counted. Size-number distributions were fitted by power law equations that allowed the identification of self-similarity
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Soil seed banks were sampled in undisturbed soil and after soil had been disturbed by tillage (tine, harrow or plough). Seeds were sorted by size and shape, and counted. Size-number distributions were fitted by power law equations that allowed the identification of self-similarity and self-affinity. Self-affinity and thus non-random size-number distribution prevailed in undisturbed soil. Self-similarity and thus randomness of size-number distribution prevailed after tillage regardless of the intensity of disturbance imposed by cultivation. The values of fractal dimensions before and after tillage were low, suggesting that short-term, short-range factors govern size-number distribution of soil seed banks. Full article
(This article belongs to the Special Issue Complex System Theory Applied to Plant Sciences)
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Review

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Open AccessReview Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations
Plants 2013, 2(1), 16-49; doi:10.3390/plants2010016
Received: 1 November 2012 / Revised: 21 December 2012 / Accepted: 16 January 2013 / Published: 25 January 2013
Cited by 2 | PDF Full-text (856 KB) | HTML Full-text | XML Full-text
Abstract
Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to
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Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. Full article
(This article belongs to the Special Issue Complex System Theory Applied to Plant Sciences)

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